More than 60% of the areas in Taiwan are referred to the mountain area and the mountainside area, especially, in the mountain area, the shape thereof is steep, the water flows therein are rapid, the structure thereof is complicated, the rock property therein is fragile and the soil therein are soft. Besides, the average rainfall in the mountain area reaches 2,500 millimeter per year, which is the three times of the average rainfall of the whole world. In particular, after the 921 Earthquake in 1999, the shallow layer of the soil becomes loose and every time when the typhoon or the torrential rain comes, it is very easy to trigger the landslide. The direct effect of the landslide is that the soil is scrubbed and glided along the gully, the valley and the river to the downstream area and aggregated in the bottom of the dam that makes the dam's capacity descended, makes the water pollution, makes the domestic water short and economic loss. If the landslide area fails to be recovered quickly, the rain will scrub the surface soil and rock and further descend the capacity and the life of the dam. Therefore, for effectively managing the dam, the forest and the mountainside, recovering the landslide area and providing the preventing and the rescuing support, it is necessary to do the effective and precisely investigation.
The mainly conventional investigation schemes are that 1) sending people to the scene to measure and survey or 2) automatically or manually recognizing the scope of the ground surface change by using the remote sensing data. The scene measurement and survey is the most precise and reliable manner, but it is ineffective, expensive, and easily affected by the terrain, the weather and traffic. The remote measurement technique using the aerial photos and the satellite image have the characters, such as the larger observation scope, the less dead space and the capability to repeatedly observe with the time line, that make the observer quickly obtain the data of the ground surface without the limitation of the sense, time and space. So far, the broadest used remote measurement sources include the aerial photos (stereo-pairs and orthophoto), the optic satellite image (orthophoto image), the synthetic aperture radar (SAR), the ground and the airborne light detection and ranging (LiDAR), and the follows are the discussions of the relevant survey techniques using the remote measurement in the respects of the data and the skills.
Aerial Photos
This technique uses the aerial photographic stereo-pairs and the manual stereo measurement for detecting. Using this technique can obtain the highly precise ground surface change in the small area, but needs lots of the manpower and the time and fails to rapidly and effectively provide the user with the relevant data for helping the survey and estimation of the disaster. According to the references and the experience, the manual detection has six visual criteria including the hue, the location, the shape, the orientation, the slope and the shadow, as showed in Table 1. From the point of view for automatic detection, the appropriateness of the criteria is discussed as follows. Regarding the hue criterion, the possible range is obtained by automatically extracting from the color information of the aerial photos. Regarding the location criterion, the possible sites of the ground surface change is extracted by using other auxiliary data, such as the roads, the mountain ridges and the rivers, to produce the buffer areas for overlaying on the image. Regarding the shape criterion, the data are obtained by using the morphology of the topography, but this part is the hardest part to be detected by the automatic method. Regarding the detection of the orientation, the possible sites of the ground surface change is detected by using the digital elevation model (DEM) to calculate the slope direction and cooperating with the river information. The slope can also be calculated by using the DEM. The shadow is a sensing factor, which is mainly used to detect the rise and fall of the ground surface and hard to be performed by the automatic method. Therefore, in the manual detection process, the 3D image is simulated by using the stereo observation, or by cooperating the orthophoto and the DEM. Accordingly, the detection criteria mentioned above are not so appropriate to be the necessary conditions of the automatic detection.
TABLE 1detectioncriteriacontenthuebrown, dark brown, light brown, green-brownlocationthe ridge around, the river-impacting slope, the road ∘shapethe bar type, the spoon type, the dendritestream-assembling site, the triangle or the rectangle in thevalleyorientationthe gravity direction of the slope and the stream directionare orthogonalslopethe sloping fieldshadowthe shadow effect is used to tell the valley and the ridgefor establishing the 3D imageThe Satellite Image
The technique of determining the landslide by using the satellite ortho-image is similar to that by using the aerial photos, but since the limitation of the space resolution of the satellite image, it more depends on the variation analysis in the different time. After comparing these two techniques, it is found that the result of the landslide automatically detected by using the satellite image is less than that manually determined by using the aerial photos both in numbers and area, thus the automatic detection by using the satellite image is still not good enough for the engineering application. However, since the satellite image has high time resolution and large shooting range that can quickly precede the ground surface survey after the disaster. Furthermore, when doing the ground surface determination by using a single satellite image, because lack of the third dimension information, it should combine with the DEM to establish the stereo-vision simulation to assist the manual determination and editing and that avoids misclassifying landslide from the flat barren land.
The Airborne Light Detection and Ranging (LiDAR)
There were several researches which use the airborne LiDAR to scan the landslide sites made by the 921 Earthquake. After the practically verifying, it is found that the accuracy of the scanning achieves the scale of 12 cm, but there is no discussion about the subjects, the landslide detection and determination, in these reports. Nevertheless, the airborne LiDAR data can be used to obtain the high solution DEM and generate the 3D image, and the 3D image is analyzed by using the 3D analysis method to obtain the roughness of the ground. Furthermore, the ground surface morphology can be analyzed by using the DEM, the 3D image and the roughness. Through the above mentioned geomorphologic analysis, the characters and the mechanism of the landslide can be further understood, and the active landslide can be estimated. Moreover, such high resolution DEM can also be used to analyze the roughness, the slope, the orientation, the semi-variance and the fractal dimension of the ground surface to study the morphology, the components and the activities of the landslide.
In the above study, the DEM with the grid scale of 1.8 meters, the shaded relief map, the slope map, the contour map and the sectional drawings of the topography . . . etc are obtained and established by using the airborne LiDAR with the point cloud density of 1 point per square meter. The mechanism of the ground surface change both in the time scale and the space scale are analyzed through the ground surface morphology and the landslide range is determined by further analyzing the topography. There are around the one-third of LiDAR point cloud that reach the ground under the trees, so the DEM from the LiDAR is more adventure for determining the long term landslide than the DEM from the aerial photos generated by the image matching and the manual editing. However, for the ground surface changing of the exposed soil, the boundary of the range of the ground surface change is drew more precisely by using the aerial photos. Moreover, there is no research using the airborne LiDAR to detect the range of the ground surface change automatically in the relevant references. The fitness for the remote detecting data in the ground surface change investigation
Accordingly, the ground surface change investigation methods that are performed by using the remote detecting data mentioned above can be categorized as the table 2 in the fitness. The accuracy portion refers to the position accuracy of the boundary of the change range in the plane coordinate, wherein the size is decided by the space resolution of the data, so the high accuracy can express the decimeter level, the middle accuracy can express the 1 meter level and the low accuracy can express the 10 meters level. The accuracy of the LiDAR image in the elevation detection can reach to centimeter level even the millimeter level, but the accuracy of the LiDAR image in the plane position is lower in contrast, so the position accuracy of the ground surface boundary estimation is low.
Please refer to the table 2, the term “investigation range” is distinguished by the data obtained from the high altitude or the ground surface. The ground surface change of the small area is not defined strictly so far, the current standard is that the long axle of the change site is smaller than 50 meters, and the conventional method defines it by using the area of the three pixels of the SPOT satellite multi-spectrum orthophoto, i.e. around 468.75 m2 (=12.5×12.5×3).
The term “instantaneity” refers to how much time for the complete of investigating disaster range or the ground change states after the disaster happened, i.e. the more time it spends, the lower instantaneity it is, and the weather condition is the most variable factor to affect the instantaneity. Except the weather condition, the satellite image schedule and the data transporting time, the gain of the grounded remote detecting data is not easy to achieve the instantaneity, and the satellite image has higher time resolution than the aerial photos, so the satellite image has higher instantaneity in contrast.
The term “automation level” telling the level of the automation mainly depends on the data property and relates to data procession technology and how much handwork involved. The aerial photographic stereo-pairs needs more handwork and the direct corresponding relationship between the stereo-pairs image and the space-coordinate is lower, so the stereo-pairs has lower automation level. Regarding the ortho-photo and the airborne LiDAR, because the data thereof have already been integrated with the geography coordinate, they can quickly detect the change of the ground surface change through the proper algorithm to reach a level of the automation. However, the high level automation does not mean the high accuracy and the high reliability. Although the subsequent manual determination cannot be avoided, the detecting ability of the algorithm highly reduces the level of the involved handwork.
TABLE 2investi-small areaauto-gationlandslidemationaccuracyrangedetectinginstantaneitylevelaerial highlargeavailablemiddleLowphotographicstereo-pairsaerial highlargeavailablemiddlehighphotographic ortho imageSPOT lowlargeunavailablehighhighsatellite ortho imageSAR lowlargeunavailablelowhighsatellite imageHigh middlelargeavailablehighhighresolution satelliteortho imageairborne highlargeavailablemiddlelowLiDAR(manually determinedaccording to thetopography)
In order to overcome the drawbacks in the prior art, an improved image processing method and system thereof are provided. The particular design in the present invention not only solves the problems described above, but also is easy to be implemented. Thus, the invention has the utility for the industry.